Heat exchange belongs to the class of basic thermal processes which occur in a range of industrial technologies, particularly in the energetic, chemical, polymer and rubber industry. The process of heat exchange is often implemented by through-flow heat exchangers. It is apparent that for an exact theoretical description of dynamics of heat exchange processes it is necessary to use partial diff...

this paper employs nonlinear disturbance observer (ndo) for robust trajectory-free nonlinear model predictive control (nmpc) of biped robots. the ndo is used to reject the additive disturbances caused by parameter uncertainties, unmodeled dynamics, joints friction, and external slow-varying forces acting on the biped robots. in contrary to the slow-varying disturbances, handling sudden pushing ...

igestion is a hot topic in pulp production at Skeena Cellulose in Prince Rupert, British Columbia, Canada. A new continuous digester control system uses a new predictive adaptive process controller to provide closed-loop control of Effective Alkali and reduced Kappa Number variability. The installation of this controller has resulted in production cost savings of $0.60 per ton of pulp and proje...

Neural network model predictive controllers have demonstrated high potential in the non-conventional branch of nonlinear control. However, the major issue in process control of nonlinear systems is the sensitivity to parameters variations and uncertainties. Indeed, when the process is controlled by neural network model predictive control (NNMPC) and subject to parameters variations or uncertain...

In this paper, we study the optimization of traffic light controllers and present an adaptive, predictive, and statistical optimization algorithm that performs dynamic queue length estimation. The system presented focuses on low power consumption, easy maintenance, and simple construction. The highlights of the system are (1) dynamic queue length estimation for timer delay computation and (2) t...

Adaptive model predictive control is applied to the control of consistency. The process model used for the control is updated on the basis of the operation conditions. The process gain is calculated by the mass balance equations or by using the preceding consistency measurement. The process dynamics is determined on the basis of the scheduling variable, i.e. the flow rate. The performance of th...

This paper investigates the application of fuzzy model and generalised predictive control strategy for the construction of a model-based predictive fuzzy controller for non-linear processes. In this method a GPC controller is used with the Takagi Sugeno Kang (TSK) piece-wise fuzzy modeling approach in an adaptive strategy. The developed method is applied to control a continuous stirred tank rea...